Image processing apparatus, image processing method, computer program and computer readable recording medium

ABSTRACT

Provided is an image processing method. The image processing method includes receiving images acquired from a plurality of vehicles positioned on a road; storing the received images according to acquisition information of the received images; determining a reference image and a target image based on images having the same acquisition information among the stored images; performing an image registration using a plurality of feature points extracted from each of the determined reference image and target image; performing a transparency process for each of the reference image and the target image which are image-registered; extracting static objects from the transparency-processed image; and comparing the extracted static objects with objects on map data which is previously stored and updating the map data when the objects on the map data which is previously stored and the extracted static objects are different from each other.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation application of U.S. application Ser.No. 16/226,759 filed on Dec. 20, 2018 which is a continuationapplication of U.S. application Ser. No. 15/822,705 filed on Nov. 27,2017, which claims priority to Korean Patent Application Nos.10-2016-0158832 filed on Nov. 26, 2016, and 10-2017-0148115 filed onNov. 8, 2017, with the Korean Intellectual Property Office, the entiredisclosures of which are incorporated herein by reference.

BACKGROUND OF THE INVENTION 1. Field of the Invention

The present invention relates to an image processing apparatus, an imageprocessing method, a computer program, and a computer readable recordingmedium, and more particularly, to an image processing apparatus, animage processing method, a computer program, and a computer readablerecording medium for providing a map having high accuracy using imagesobtained through cameras.

2. Description of the Related Art

Although automakers are recently trying to implement an autonomousvehicle with a higher level of advanced driver assistance system (ADAS),they are facing limitations due to the technical problems ofconventional systems using sensors such as cameras and radar. In orderto overcome such a limitation, the automakers try to find a solutionutilizing additional information system to implement the autonomousvehicle, and an example of the representative additional informationsystem is a detailed map.

The detailed map refers to a map including information on positions andtypes of all fixed objects on the road, and the detailed map serves tocomplement performance of the sensor in a situation in which it isdifficult for the sensor to normally operate. In a case in whichinformation of the sensor is not correct due to obstacles or badweather, the vehicle may complement the incorrect information byutilizing information of the detailed map.

Since the detailed map should provide information on the positions andtypes of all fixed geographic features on the road, it is important toquickly reflect accuracy of the map and changes of an actual road andthe geographic features. However, when it is difficult to know theaccurate information on the types of fixed geographic features due tothe geographic features covered by a moving object, or changes in a roadenvironment such as an installation of a traffic light,extending/closing of the road, a change in lane information, and thelike occur, there is a problem that such information is not quicklyreflected on the actual map. Therefore, a method capable of solving sucha problem is required.

SUMMARY

An aspect of the present invention may provide an image processingapparatus, an image processing method, a computer program, and acomputer readable recording medium for creating a map.

An aspect of the present invention may also provide an image processingapparatus, an image processing method, a computer program, and acomputer readable recording medium for creating map data using imagesobtained by a camera mounted in a vehicle.

An aspect of the present invention may also provide an image processingapparatus, an image processing method, a computer program, and acomputer readable recording medium for updating map data using imagestransmitted from vehicles positioned on a road.

According to an aspect of the present invention, an image processingmethod may include receiving images acquired from a plurality ofvehicles positioned on a road; storing the received images according toacquisition information of the received images; determining a referenceimage and a target image based on images having the same acquisitioninformation among the stored images; performing an image registrationusing a plurality of feature points extracted from each of thedetermined reference image and target image; performing a transparencyprocess for each of the reference image and the target image which areimage-registered; extracting static objects from thetransparency-processed image; and comparing the extracted static objectswith objects on map data which is previously stored and updating the mapdata when the objects on the map data which is previously stored and theextracted static objects are different from each other.

The performing of the image registration may include extracting theplurality of feature points from each of the determined reference imageand target image; and performing the image registration for thedetermined images using the plurality of extracted feature points.

The plurality of feature points may be points at which image brightnessvalue suddenly changes in the reference image or the target image andmay be edges of pixels or corner points.

The transparency process may multiply R, G, and B pixel values ofrespective pixels included in the images for which the transparencyprocess is to be performed by a predetermined value smaller than 1, andthe predetermined value may be a reciprocal number of N, which is atotal number of the images for which the transparency process is to beperformed.

The acquisition information may include at least one of information onpositions at which the images are photographed, information on angles atwhich the images are photographed, and information on directions inwhich the images are photographed.

The extracting of the plurality of feature points may include extractinga plurality of first feature points from the reference image; andextracting a plurality of second feature points from the target image.

The performing of the image registration may include performing amatching operation matching a first feature point group in which theplurality of first feature points are grouped and a second feature pointgroup in which the plurality of second feature points are grouped;calculating a homography using information of matched pairs between thefirst feature point group and the second feature point group through thematching operation; converting the target image using the calculatedhomography; and registering the reference image and the converted targetimage.

The updating of the map data may include confirming position informationof the extracted static objects; examining whether or not objectsdifferent from the extracted static objects exist at a positioncorresponding to the confirmed position information of the staticobjects in the map data which is previously stored; and updating the mapdata by reflecting the extracted static objects to the map data which ispreviously stored corresponding to the position information, when thedifferent objects exist as a result of the examination.

The image processing method may further include transmitting the updatedmap data to the plurality of vehicles positioned on the road.

According to another aspect of the present invention, an imageprocessing apparatus may include a receiving unit receiving imagesacquired from a plurality of vehicles positioned on a road; a storingunit storing the received images according to acquisition information ofthe received images; a controlling unit determining a reference imageand a target image based on images having the same acquisitioninformation among the stored images; and an image processing unitperforming an image registration using a plurality of feature pointsextracted from each of the determined reference image and target imageand performing a transparency process for each of the reference imageand the target image which are image-registered, wherein the controllingunit extracts static objects from the transparency-processed image,compares the extracted static objects with objects on map data which ispreviously stored, and updates the map data when the objects on the mapdata which is previously stored and the extracted static objects aredifferent from each other.

The image processing unit may generate one synthesized image byextracting the plurality of feature points from each of the determinedreference image and target image and performing the image registrationfor the determined images using the plurality of extracted featurepoints.

The plurality of feature points may be points at which image brightnessvalue suddenly changes in the reference image or the target image and beedges of pixels or corner points.

The transparency process may multiply R, G, and B pixel values ofrespective pixels included in the images for which the transparencyprocess is to be performed by a predetermined value smaller than 1, andthe predetermined value may be a reciprocal number of N, which is atotal number of the images for which the transparency process is to beperformed.

The acquisition information may include at least one of information onpositions at which the images are photographed, information on angles atwhich the images are photographed, and information on directions inwhich the images are photographed.

The image processing unit may include a feature point extracting unitextracting a plurality of first feature points from the reference imageand extracting a plurality of second feature points from the targetimage; a feature point matching unit performing a matching operationmatching a first feature point group in which the plurality of firstfeature points are grouped and a second feature point group in which theplurality of second feature points are grouped; a homography calculatingunit calculating a homography using information of matched pairs betweenthe first feature point group and the second feature point group throughthe matching operation; an image registration unit converting the targetimage using the calculated homography and registering the referenceimage and the converted target image; and a transparency processing unitperforming a transparency process for the registered images.

The controlling unit may confirm position information of the extractedstatic objects, examines whether or not objects different from theextracted static objects exist at a position corresponding to theconfirmed position information of the static objects in the map datawhich is previously stored, and update the map data by reflecting theextracted static objects to the map data which is previously storedcorresponding to the position information, when the different objectsexists as a result of the examination.

According to another aspect of the present invention, an imageprocessing method may include selecting images for the same region amonga plurality of images photographed by a moving body; performing atransparency process for each of the selected images; registering thetransparency-processed images; and determining static objects in theregistered image based on transparencies of objects included in theregistered image.

In the selecting of the images, images having the same acquisitioninformation for each of the plurality of images may be selected, and theacquisition information may include at least one of information onpositions at which the images are photographed, information on angles atwhich the images are photographed, and information on directions inwhich the images are photographed.

The determining of the static objects may include calculating standarddeviations of a pixel value of the registered image, a pixel value ofthe reference image, and pixel values of target images for each ofpixels; and determining pixels of which the calculated standarddeviation is a predetermined value or less as pixels for the staticobjects and determining pixels of which the calculated standarddeviation exceeds the predetermined value as pixels for the dynamicobjects.

The image processing method may further include excluding the dynamicobjects from the registered image, confirming position information ofthe static objects in the registered image from which the dynamicobjects are excluded, and updating map data based on the positioninformation of the static objects.

According to another exemplary embodiment of the present invention, acomputer readable recording medium in which a program for executing animage processing method is recorded may be provided.

According to another exemplary embodiment of the present invention, acomputer program stored in a computer readable recording medium toexecute an image processing method may be provided.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram illustrating a map creating system according to anexemplary embodiment of the present invention;

FIG. 2 is a diagram illustrating a block configuration of an electronicapparatus mounted in first to third vehicles according to an exemplaryembodiment of the present invention;

FIG. 3 is a diagram illustrating a block configuration of an imageprocessing apparatus according to an exemplary embodiment of the presentinvention;

FIG. 4 is a diagram illustrating operations of a feature pointextracting unit and a feature point matching unit of an image processingunit according to an exemplary embodiment of the present invention;

FIG. 5 is a diagram illustrating a process of matching a reference imagewith a target image according to a feature point matching described inFIG. 4 according to an exemplary embodiment of the present invention;

FIG. 6 is a diagram illustrating a matching relationship between thereference image and the target image by a homography calculated by ahomography calculating unit of the image processing unit according to anexemplary embodiment of the present invention;

FIG. 7 is a diagram illustrating a distinction between a static objectand a dynamic object according to an exemplary embodiment of the presentinvention;

FIGS. 8 to 11 are diagrams illustrating a transparency process accordingto an exemplary embodiment of the present invention;

FIG. 12 is a diagram illustrating image processing results for thereference image and the target image according to an exemplaryembodiment of the present invention;

FIG. 13 is a diagram illustrating an operation flow of an imageprocessing apparatus according to an exemplary embodiment of the presentinvention;

FIG. 14 is a diagram illustrating an operation (S1325) of FIG. 13 indetail;

FIG. 15 is a diagram illustrating a block configuration of an imageprocessing apparatus for creating a map according to another exemplaryembodiment of the present invention;

FIG. 16 is a diagram illustrating a method for creating a map of theimage processing apparatus of FIG. 15;

FIG. 17 is a diagram illustrating a block configuration of an electronicapparatus according to still another exemplary embodiment of the presentinvention;

FIG. 18 is a diagram illustrating an operation flow of the electronicapparatus of FIG. 17;

FIGS. 19 and 20 are diagrams illustrating a transparency process forfive images;

FIG. 21 is a diagram illustrating an image registration of thetransparency-processed images of FIG. 20; and

FIG. 22 is a diagram illustrating a result of the registration of theeimages of FIG. 21.

DETAILED DESCRIPTION

The following description illustrates only a principle of the presentinvention. Therefore, those skilled in the art may implement theprinciple of the present invention and devise various apparatusesincluded in the spirit and scope of the present invention although notclearly described or shown in the present specification. In addition, itis to be understood that all conditional terms and exemplary embodimentsmentioned in the present specification are obviously intended only toallow those skilled in the art to understand a concept of the presentinvention in principle, and the present invention is not limited toexemplary embodiments and states particularly mentioned as such.

Further, it is to be understood that all detailed descriptionsmentioning specific exemplary embodiments of the present invention aswell as principles, aspects, and exemplary embodiments of the presentinvention are intended to include structural and functional equivalencesthereof. Further, it is to be understood that these equivalences includean equivalence that will be developed in the future as well as anequivalence that is currently well-known, that is, all devices devisedso as to perform the same function regardless of a structure.

Therefore it is to be understood that, for example, a block diagram ofthe present specification shows a conceptual aspect of an illustrativecircuit for embodying a principle of the present invention. Similarly,it is to be understood that all flowcharts, state transition views,pseudo-codes, and the like show various processes that may tangiblyembodied in a computer-readable medium and that are executed bycomputers or processors regardless of whether or the computers or theprocessors are clearly illustrated.

Functions of various devices including processors or functional blocksrepresented as concepts similar to the processors and illustrated in theaccompanying drawings may be provided by hardware having capability toexecute appropriate software as well as dedicated hardware. When thefunctions are provided by the processors, the above-mentioned functionsmay be provided by a single dedicated processor, a single sharedprocessor, or a plurality of individual processors, in which some ofthem may be shared.

In addition, terms mentioned as a processor, a control, or a conceptsimilar to the processor or the control should not be interpreted toexclusively cite hardware having capability to execute software, butshould be interpreted to implicitly include digital signal processor(DSP) hardware and a read only memory (ROM), a random access memory(RAM), and a non-volatile memory for storing software without beinglimited thereto. The above-mentioned terms may also include well-knownother hardware.

In the claims of the present specification, components represented asmeans for performing functions mentioned in a detailed description areintended to include all methods for performing functions including alltypes of software including, for example, a combination of circuitdevices performing these functions, firmware/micro codes, or the like,and are coupled to appropriate circuits for executing the software. Itis to be understood that since functions provided by variously mentionedmeans are combined with each other and are combined with a schemedemanded by the claims in the inventions defined by the claims, anymeans capable of providing these functions are equivalent to meansrecognized from the present specification.

The above-mentioned objects, features, and advantages will becomeobvious from the following detailed description provided in relation tothe accompanying drawings. Therefore, those skilled in the art to whichthe present invention pertains may easily practice a technical idea ofthe present invention. Further, in describing the present invention, inthe case in which it is judged that a detailed description of awell-known technology associated with the present invention mayunnecessarily make unclear the gist of the present invention, it will beomitted.

Hereinafter, various exemplary embodiments of the present invention willbe described in detail with reference to the accompanying drawings.

FIG. 1 is a diagram illustrating a map creating system 10 according toan exemplary embodiment of the present invention.

Referring to FIG. 1, a map creating system 10 according to the presentinvention includes first to third vehicles 100, 110, and 120, and animage processing apparatus 130.

The first to third vehicles 100, 110, and 120 are mounted with cameras,which are apparatuses capable of obtaining images, and transmit theobtained images to the image processing apparatus 130 while beingpositioned on a road. Although FIG. 1 illustrates the vehicles, othermeans other than the vehicle, for example, a movable means such as aperson, a bicycle, a ship, a train, or the like, may also be implementedas long as they may transmit the images obtained by photographing thesubjects on the road or around the road to the image processingapparatus 130. Such a movable means will be collectively referred to asa moving body. Hereinafter, a case in which the moving body is thevehicle will be described as an example, for convenience of explanation.

Meanwhile, the subjects described above include fixed static objectsthat may be reflected in map data such as bridges, buildings, roads,sidewalks, road construction marks, speed bumps, crosswalks,intersections, traffic lights, median strips, bus stops, directionalsigns, and the like.

Further, the image processing apparatus 130 according to an exemplaryembodiment of the present invention may process images received from thefirst to third vehicles 100, 110, and 120 to create an electronic map,and may transmit the created electronic map to other vehicles positionedon the road including the first to third vehicles 100, 110, and 120.

Further, the image processing apparatus 130 according to an exemplaryembodiment of the present invention may also be a map creating server.

FIG. 2 is a diagram illustrating a block configuration of an electronicapparatus 200 mounted in the first to third vehicles 100, 110, and 120according to an exemplary embodiment of the present invention.

Referring to FIG. 2, an electronic apparatus 200 according to thepresent invention includes an input unit 210, a communicating unit 230,a camera unit 240, and a controlling unit 250, and may further include adisplay unit 220. As an example, the electronic apparatus 200, which isan apparatus capable of photographing an image, may be a mobile terminalsuch as a smartphone including a vehicle video camera or a camera.Further, the electronic apparatus 200 may be embedded in the vehicle soas to be connected to an electronic controller unit (ECU) of the vehiclethrough controller area network (CAN) communication, and may also be amobile terminal which may be held in the vehicle such as the smartphoneof the user and may transmit and receive data by being connected to amobile communication system.

The inputting unit 210 may receive a command or the like for performingan operation from the user and may include a key-pad, a dome switch, atouch pad (resistive/capacitive), a jog wheel, a jog switch, a pushswitch, or the like.

The communicating unit 230 may transmit the image photographed by thecamera unit 240 to the image processing apparatus 300, or transmit thephotographed image to other communication means included in the vehicle.The communicating unit 230 may perform communication in a wiredcommunication scheme as well as various wireless communication schemessuch as Bluetooth, Wi-Fi, wireless broadband, 3rd generation (3G), WCDMAscheme, long term evolution (LTE), and a 4th generation (4G)communication schemes.

The camera unit 240 converts an image signal (e.g., light) received fromthe outside into a specific electric signal to generate image data. Forexample, the camera unit 240 may obtain image data of the inside andoutside of the vehicle related to the driving of the vehicle.

The display unit 220 may output visual information to the user, and mayoutput a map or an image photographed during the driving. The displayunit 220 and the input unit 210 may be integrally formed as a touchpanel or a touch screen.

The controlling unit 250 generally controls the electronic apparatus200, for example, the controlling unit controls the camera unit 240 soas to photograph the image, and transmits the photographed image to theimage processing apparatus 130 through the communicating unit 230. Inaddition, since the controlling unit 250 also transmits acquisitioninformation including at least one of photographed position informationof the image, photographed angle information thereof, and photographeddirection information thereof when transmitting the image photographedby the camera unit 240 to the image processing unit 300 through thecommunicating unit 230, the image processing apparatus 300 according tothe present invention may classify the received images according to theacquisition information, thereby making it possible to quickly updatethe map data only for a point at which the static object is changed.Further, the controlling unit 250 may perform a camera calibrationprocess for adjusting camera parameters for the image photographed bythe camera unit 240 and transmit it to the image processing apparatus300 through the communicating unit 230.

Meanwhile, the electronic apparatus 200 mounted in the first to thirdvehicles 100, 110, and 120 may photograph the object in units ofpredetermined time, and transmit images of the photographed object tothe image processing apparatus 300. As an example, the electronicapparatus 200 may photograph the object in unit of one minute andtransmit images of the photographed object to the image processingapparatus 300. Since the images of the photographed object includeinformation on a photographed time and place, the photographed imagesmay be classified by the same place.

Further, according to an exemplary embodiment of the present invention,the controlling unit 250 of the electronic apparatus 200 may correctparameters such as positions, angles, features, and the like of thecameras installed in the respective vehicles through camera calibration.The reason for performing such a camera calibration process is that thephotographed place and target of the images photographed by the camerasare the same as each other, but installation heights, angles, and thelike of the cameras photographing the respective images are differentfrom each other, and therefore, an image registration may be easilyperformed only by correcting such characteristic parameters of thecamera.

Hereinafter, it is assumed that since the electronic apparatus 200 ismounted in the first to third vehicles 100, 110, and 120, the first tothird vehicles 100, 110, and 120 photograph the images and transmit thephotographed images to the image processing apparatus 130.

FIG. 3 is a block configuration of an image processing apparatus 300according to an exemplary embodiment of the present invention. Referringto FIG. 3, the image processing apparatus 300 according to the presentinvention includes all or some of a controlling unit 305, a receivingunit 310, a transmitting unit 315, a storing unit 320, and an imageprocessing unit 330.

The receiving unit 310 receives images acquired by the cameras mountedin a plurality of vehicles positioned on the road and acquisitioninformation including at least one of information on positions at whichthe acquired images are photographed, information on angles at which theacquired images are photographed, and information on direction in whichthe acquired images are photographed through wireless communication suchas long term evolution (LTE) or Wi-Fi, or wired communication.

The reason that the receiving unit 310 receives the acquired informationother than the images is to allow the controlling unit 305 to easilyclassify the acquired images for image processing. Specifically, sincethe images acquired at the same point may have different photographingdirections and angles, it is preferable that the controlling unit 305classifies the images in consideration of the different photographingdirection and angles and then performs the image processing according toan exemplary embodiment of the present invention.

For example, when the vehicle enters an intersection, the imageprocessing apparatus 300 according to the exemplary embodiment of thepresent invention should be able to confirm whether the acquired imageis an image acquired while the vehicle enters the intersection in eitherdirection, so that the target images may be accurately selected.

That is, in the case of the intersection of four directions, since thevehicle may acquire the images while entering in the four directions,respectively, it is possible to accurately create or update map dataaround the intersection only in a case in which the image processingapparatus 300 may distinguish the photographed directions of therespective images.

Further, in a case in which the image processing apparatus 300 accordingto the exemplary embodiment of the present invention considers theinformation on the photographed angles of the acquired images, it ispossible to create or update the map data through a more accurate imageprocessing.

The transmitting unit 315 transmits the map data updated or the map datastored in the storing unit 320 by the controlling unit 305 to theelectronic apparatus 200 of the vehicle of the user or the mobileterminal of the user by a control of the controlling unit 305.

The controlling unit 305 classifies the map data and the images receivedthrough the receiving unit 310 according to the acquired information ofthe received images and stores them in the storing unit 320. The mapdata is stored in a map data storing unit 320 a as map data which iscreated previously, and the received images are each stored in areceived image storing unit 320 b. The controlling unit 305 may performthe image processing for images having the same position information,direction information, or the like using the classified and storedimages, according to the exemplary embodiment of the present invention.Here, the storing unit 320 may be implemented as an embedded type ofstorage element such as a random access memory (RAM), a flash memory, aread only memory (ROM), an erasable programmable ROM (EPROM), anelectronically erasable and programmable ROM (EEPROM), a register, ahard disk, a removable disk, a memory card, or the like, as well as aremovable type of storage element such as a USB memory, or the like.

Such a storing unit 320 may be implemented within the image processingapparatus 300, and may be implemented in a type of external database(DB) server connected to the image processing apparatus 300.

Meanwhile, the controlling unit 305 determines a reference image and atarget image based on images having the same acquired information amongthe images stored in the received image storing unit 320 b, performs animage registration using a plurality of feature points extracted fromthe determined reference image and target image, respectively, andcontrols the image processing unit 330 so that a transparency process isperformed for the image registered images. Here, the reference imagerefers to an image that is a reference for the image registration, andthe target image refers to an image that is a target for the imageregistration.

Further, the controlling unit 305 registers the imagestransparency-processed by the image processing unit 330, and controlsthe image processing unit 330 to detect a static object region from theregistered image. In this case, the image processing unit 330 may eachcalculate standard deviations of a pixel value of the registered image,a pixel value of the acquired reference image, and pixel values of thetarget images converted according to a homography for each of thepixels, and may detect a static object region from the registered imagebased on the calculated standard deviation.

In addition, the controlling unit 305 compares detected static objectswith objects on the map data which is previously stored, and updates themap data stored in the map data storing unit 320 a, when the objects onthe map data which is previously stored are different from the extractedstatic objects.

Meanwhile, the image processing unit 330 may each calculate standarddeviations of a pixel value of the registered image, a pixel value ofthe acquired reference image, and pixel values of the target imagesconverted according to a homography for each of the pixels, and maydetect a dynamic static object region from the registered image based onthe calculated standard deviation. In this case, the controlling unit305 may exclude the detected dynamic object from the registered image.In addition, the controlling unit 305 may confirm position informationof the static object in the registered image from which the dynamicobject is excluded, and may update the map data based on the positioninformation of the static object.

The image processing unit 330 in FIG. 3 calculates a homography byextracting feature points between the acquired images and matching thefeature points between the respective images to calculate the matchedfeature points having common feature points. In addition, the imageprocessing unit 330 registers the images acquired by using thecalculated homography.

The image processing unit 330 according to an exemplary embodiment ofthe present invention includes all or some of a feature point extractingunit 330 a, a feature point matching unit 330 b, a homographycalculating unit 330 c, an image registration unit 330 d, a transparencyprocessing unit 330 e, and an image synthesizing unit 330 f.

Here, the image processing unit 330 may be implemented in a separatemodule using software, hardware, or a combination thereof. As anexample, according to a hardware implementation, the image processingunit 330 may be implemented using at least one of application specificintegrated circuits (ASICs), digital signal processors (DSPs), digitalsignal processing devices (DSPDs), programmable logic devices (PLDs),field programmable gate arrays (FPGAs), processors, controllers,micro-controllers, microprocessors, and electrical units for performingother functions.

An operation of the image processing unit 330 according to an exemplaryembodiment of the present invention will be described with reference toFIGS. 4 to 12. FIG. 4 is a diagram illustrating operations of a featurepoint extracting unit 330 a and a feature point matching unit 330 b ofan image processing unit 330 according to an exemplary embodiment of thepresent invention and FIG. 5 is a diagram illustrating a process ofmatching a reference image with a target image according to a featurepoint matching described in FIG. 4 according to an exemplary embodimentof the present invention.

FIG. 6 is a diagram illustrating a matching relationship between thereference image and the target image by a homography calculated by ahomography calculating unit 330 c of the image processing unit 330according to an exemplary embodiment of the present invention.

FIG. 7 is a diagram illustrating a distinction between a static objectand a dynamic object according to an exemplary embodiment of the presentinvention. FIGS. 8 to 11 are diagrams illustrating a transparencyprocess according to an exemplary embodiment of the present invention.

FIG. 12 is a diagram illustrating image processing results for thereference image and the target image according to an exemplaryembodiment of the present invention. The feature point extracting unit330 a extracts a plurality of feature points from each of the referenceimage and the target image determined by the controlling unit 305. Here,the plurality of feature points extracted from the reference image andthe target image, which are points at which an image brightness valuesuddenly changes in the reference image or the target image, may beedges of pixels or corner points. Specifically, an operation ofextracting the feature points by the feature point extracting unit 330 aaccording to an exemplary embodiment of the present invention will bedescribed with reference to FIG. 4.

In FIG. 4, reference numerals 405 and 410 denote images photographed atthe same place and denotes images in which the camera calibrationprocess is completed. It is assumed in FIG. 4 that the image ofreference numeral 405 and the image of reference numeral 410 areregistered, and accordingly, the image of reference numeral 410 refersto the reference image that is a reference for the image registration,and the image of reference numeral 405 refers to the target image thatis a target for the image registration.

In FIG. 4, the feature point extracting unit 330 a each extracts thefeature points from the reference image 410 and the target image 405,where reference number 415 is a diagram illustrating the feature pointsextracted from the target image 405, and reference numeral 420 is adiagram illustrating the feature points extracted from the referenceimage 410.

The feature extraction of the respective images refers to extractingcharacterized points from the respective images, and as an example,points at which the image brightness value suddenly changes, such asedges of pixels or corner points in the images may correspond to thefeature points. As algorithms for extracting the feature points of therespective images, a Harris scheme, a scale invariant feature transform(SIFT) scheme, an oriented fast and rotated brief (ORB) scheme, afeatures from accelerated segment test (FAST) scheme, and the like maybe used.

An image of reference numeral 415 illustrates feature points determinedas the feature points in the image of reference numeral 405 by applyingthe FAST scheme, and an image of reference numeral 425 illustratesfeature points determined as the feature points in the image ofreference numeral 410 by applying the FAST scheme.

Reference number 415 a illustrates one of the feature points extractedfrom reference numeral 415, and reference numeral 415 b illustrates afirst feature point group in which the plurality of feature pointsextracted from reference numeral 415 are grouped. In addition, referencenumber 420 a illustrates one of the feature points extracted fromreference numeral 420, and reference numeral 420 b illustrates a secondfeature point group in which the plurality of feature points extractedfrom reference numeral 420 are grouped.

According to an exemplary embodiment of the present invention, when thefeature point extracting unit 330 a completes the extraction of thefeature points such as reference numerals 415 and 420, the feature pointmatching unit 330 b matches the feature points of the reference imageand the target image using the first feature point group 415 b extractedfrom the reference image and the second feature point group 420 bextracted from the target image such as reference numeral 430. Thefeature point matching according to the present invention refers tomatching the feature points extracted from the respective images to eachother to find common feature points existing between the reference imageand the target image, and may use a random sample consensus (RANSAC)scheme. The RANSAC scheme is a method of selecting data in which aconsensus is maximally formed by randomly selecting sample data fromdata, and is a method capable of more accurately matching the featurepoints by acquiring the data in which error and noise are minimized inthe data.

Reference numeral 430 illustrates a matching relationship between theimage 415 and the image 420 by matching the extracted feature pointsbetween the image 415 on which the feature points extracted from thetarget image 405 are marked and the image 420 on which the featurepoints extracted from the reference image 410 are marked. Examples ofthe method of matching the feature points of the respective images mayinclude a least square method, M-estimator SAC (MSAC), maximumlikelihood SAC (MLESAC), locally optimized RANSAC (LO-RANSAC), and thelike other than the RANSAC scheme.

When the feature points of the reference image and the feature points ofthe target image are matched by the feature point matching unit 330 b,the homography calculating unit 330 c calculates a homography, which isa transformation matrix between the reference image and the targetimage, using information of matched pairs between the first featurepoint group 415 b and the second feature point group 420 b.

The homography is a transformation matrix for matching a target image ofa 2D plane to the reference image. In order to determine the homography,at least four matched pointed are required in the respective images, anda relationship matrix H between the matched points is defined as a 3×3matrix H as in <Equation 1>.

$\begin{matrix}{{w\begin{bmatrix}x^{\prime} \\y^{\prime} \\1\end{bmatrix}} = {\begin{bmatrix}{h\; 11} & {h\; 12} & {h\; 13} \\{h\; 21} & {h\; 22} & {h\; 23} \\{h\; 31} & {h\; 32} & {h\; 33}\end{bmatrix}\begin{bmatrix}x \\y \\1\end{bmatrix}}} & \left\lbrack {{Equation}\mspace{14mu} 1} \right\rbrack\end{matrix}$

Here, x and y denote feature point coordinates of the reference image,and ‘1’ means that the reference image and the target image arehomogenous to each other. W, which is a weight, is defined as aconstant, not ‘0’. The 3×3 matrix is the transformation matrix H.

FIG. 6 is a diagram illustrating a matching relationship between thereference image and the target image according to an exemplaryembodiment of the present invention. In FIG. 6, reference numeral 600denotes a reference image, reference numeral 605 denotes a target image,and reference numeral 610 illustrates that a matching relationshipbetween a feature point matrix (x, y, 1) of the reference image and afeature point matrix (x′, y′, 1) of the target image exists using thecalculated homography matrix.

The image registration unit 330 d converts the target image 410 to beregistered to the reference image 405 using the homography calculated bythe homography calculating unit 330 c.

Specifically, in FIG. 5, reference numeral 505 denotes the referenceimage 410 in FIG. 4 and reference numeral 510 denotes an image obtainedby converting the target image of reference numeral 405 in FIG. 4 usingthe homography matrix calculated by the homography calculating unit 330c. In addition, the image registration unit 330 d registers thereference image 505 and the converted target image 510 as in referencenumeral 515 of FIG. 5. As illustrated in FIG. 5, the image registrationunit 330 d performs the registration based on the matched feature pointsof the respective images and naturally registers two different images byblending different images.

The transparency processing unit 330 e performs a transparency processfor each of the reference image and the target image which areregistered by the image registration unit 330 d.

An operation of performing the transparency process by the transparencyprocessing unit 330 e according to an exemplary embodiment of thepresent invention will be described in detail with reference to FIGS. 8to 11. The transparency process performed by the transparency processingunit 330 e according to the present invention may be performed as in amethod described in FIGS. 8 to 11. A total of ten images exist in FIG.8, a first FIG. 800 of a circular shape exists in all of the ten images,a second FIG. 810 of a triangular shape exists in five images, and athird FIG. 820 of a quadrangular shape exists in three images. In thisstate, when the respective images are converted with a predeterminedtransparency, pixel values of the first to third FIGS. 800, 810, and 820decrease as illustrated in FIG. 9, thereby causing a blurring effect.Thereafter, when the respective images which are transparency-processedare overlapped with each other, as illustrated in FIG. 10, the firstFIG. 800 has the same clear shape as before the transparency process,but the second FIG. 810 and the third FIG. 820 have lower definitionthan before the transparency process.

As described above, a method of performing a transparency process forthe target image in the transparency processing unit 330 e according toan exemplary embodiment of the present invention includes performing animage processing such that a transparency target image has a pixel valuesmaller than the pixel value of the original image by multiplying eachpixel value (0 to 255) of the transparency target image by apredetermined constant. In general, R, G, and B pixel values of eachpixel have values of 0 to 255, and when the pixel value has a smallvalue, each pixel is visually blurred, and as a result, the entire imageis also blurred.

As illustrated in FIG. 11, according to an exemplary embodiment of thepresent invention, assuming that N images are registered, when it isassumed that transparency of images for which the transparency processis not performed is ‘1’, the transparency process may be performed bymultiplying pixel values of the respective image to be transparentizedby 1/N. FIG. 9 illustrates transparency of each image of a case ofmultiplying a pixel of each image by 1/10 because the total number oftransparency target images is ten. Here, in FIG. 11, a 0-th image is thereference image, and first to N−1-th images are the target imagesconverted by the homography.

When the N images transparentized as described above are registered, thestatic objects existing in each image remain on the registered image asit is, but the dynamic objects disappear. That is, when the respectiveimages are transparentized and then registered, since the pixelcorresponding to the static object in each image is in a state in whichthe transparency multiplied by the same constant is applied, in a casein which the respective pixel values are added, the added pixel value isequal to an original pixel value or is close thereto, and as a result,the respective image also exists on the registered image as it is.

An operation of extracting the static object through the transparencyprocess according to an exemplary embodiment of the present inventionwill be again described in detail. First, a pixel value for each ofpixels of the registered image generated by registering the referenceimage and the target image converted according to the homography iscalculated. Here, the calculated pixel value for each of the pixels ofthe registered image is equal to an average value of each of pixels ofthe N registered images.

In addition, standard deviations of the calculated pixel value of theregistered image, the pixel value of the acquired reference image, andthe pixel values of the converted target images are calculated for eachof the pixels. The image processing apparatus 300 according to anexemplary embodiment of the present invention may determine a pixelhaving a value within a predetermined threshold value among thecalculated standard deviations as a pixel configuring the static object.

On the contrary, the image processing apparatus 300 according to anexemplary embodiment of the present invention may determine a pixelhaving a value exceeding a predetermined threshold value among thecalculated standard deviations as a pixel configuring the dynamicobject. With such a scheme, the image processing apparatus 300 mayclassify the static object and the dynamic object from the registeredimage by calculating the standard deviations of the pixel values of therespective image and the pixel values of the registered image.

As such, the reason that the image processing apparatus 300 may classifythe static object and the dynamic object from the average value for eachof the pixels of the registered image is because the static objectexists per each acquired image and a change of the pixel value for eachof the respective images is small, such that the standard deviation ofthe pixel values included in the static object is lower than apredetermined threshold value.

On the other hand, since the dynamic object does not exist per theacquired image but exists only in some images, a change of the pixelvalue for each of the respective images is large, and accordingly, thestandard deviation of the pixel values included in the dynamic object ishigher than the predetermined threshold value. Here, the predeterminedthreshold value may be determined by an experiment.

In addition, the background other than the roads, the traffic lights,the crosswalks, and the buildings may exist in the static objectsextracted according to an exemplary embodiment of the present invention.In this case, according to the present invention, in order to create themap, it is necessary to identify only the static objects to be reflectedto the actual road data among the extracted static objects through anadditional method, where the extracted static objects may be identifiedthrough a deep learning or a machine learning. Therefore, thecontrolling unit 305 of the image processing apparatus 300 according toan exemplary embodiment of the present invention may separate only thestatic objects such as the traffic lights, the roads, the crosswalks,and the like necessary to create or update the map data from theextracted static objects through the deep learning or the machinelearning.

In FIG. 9, in a case in which the transparency processing unit 330 emultiplies the pixel value of each image by 1/10 for the transparencyprocess of each image and registers ten images, it may be confirmed thatthe first FIG. 800 exists in the same way as before performing thetransparency process, but the second and third FIGS. 810 and 820disappear as compared to before performing the transparency process, asillustrated in FIG. 10. FIG. 10 illustrates a case in which the imageregistration for ten images is performed, but when an infinite number ofimages are overlapped, the dynamic objects having a large change of thepixel value between the images will be recognized as nonexistent.

The contents of overlapping the respective images will be describedusing <Equation 2> below.

A(t)=α(A(t−1))+(1−α)f(t),1≤t≤N−1  [Equation 2]

Here, A(t) uses a t−1-th image and a t-th image as average imagesobtained for t time. Further, α, which is a weight, has a value of 0.5and refers to add a 50% pixel value of the t−1-th image and a 50% pixelvalue of the t-th image. Further, f(t) denotes the t-th image.

As an example, Equation 2 will be applied as follows.

A(1)=αf(0)+(1−α)f(1),

A(2)=α(A(1))+(1−α)f(2),

A(3)=α(A(2))+(1−α)f(3)

Further, the image processing apparatus 300 may perform an imageprocessing using the images received in units of predetermined periodsuch as one day or one week, and may perform the image processing usingall of the received images or using an arbitrarily selected image. As anexample, as illustrated in FIG. 11, if there are N images from 0 to N−1acquired by photographing a specific region for one day by the first tothird vehicles 100, 110, and 120 and transmitted to the image processingapparatus 300, the image processing apparatus 300 may also extract thestatic objects by performing the transparency process and registrationfor the entirety of the images from 0 to N−1, and may also extract thestatic objects only using some of the entirety of the images.

A method of extracting, by the controlling unit 305 of the imageprocessing apparatus 300, the static objects such as the buildings, theroads, and the like from the images transparentized by the transparencyprocessing unit 330 e according to the contents described above will bedescribed.

In FIG. 7, reference numerals 740 and 750, which are images photographedat a predetermined time interval in a specific region, are imagephotographed by the cameras or smart phones mounted in the vehicles. Thephotographed images include a building 700, a road 720, and a trafficlight 730 as the static objects and include vehicles 710 as the dynamicobjects. The image processing apparatus 300 may acquire a plurality ofimages related to the specific region by classifying only the imagesrelated to the specific region using acquisition information of theimages received from the electronic apparatus 200 for a predeterminedtime (e.g., ‘one day’).

In addition, when the image processing apparatus 300 performs the imageregistration and the transparency process for the received images, thestatic objects such as the building 700, the road 720, and the trafficlight 730 exist as it is, but the dynamic objects such as the vehiclesdisappear, as illustrated by reference numeral 760. According to anexemplary embodiment of the present invention, as the number of theregistered images is increased, the static object and the dynamic objectmay be more clearly classified when the transparency process isperformed.

The image synthesizing unit 330 f performs synthesis for thetransparency-processed images and transmits the synthesized image to thecontrolling unit 305.

The storing unit 320 includes a map data storing unit 320 a and areceived image storing unit 320 b. The map data storing unit 320 a storemap data which is previously created and also store map data which isupdated by the controlling unit 305. The received image storing unit 320b stores the image received through the receiving unit 310.

The controlling unit 305 according to an exemplary embodiment of thepresent invention performs a control so that the images received throughthe receiving unit 310 are stored in the received image storing unit 320b, and updates the map data when it is necessary to update the storedmap data to store the updated map data in the map data storing unit 320a.

In addition, the controlling unit 305 extracts the static objects fromthe images transparency-processed by the image processing unit 330,compares the extracted static objects with objects on the map data whichis previously stored in the map data storing unit 320 a, and updates themap data when the objects on the map data which is previously stored andthe extracted static objects are different.

Specifically, the controlling unit 305 confirms position information ofthe extracted static objects and examines whether or not the objectsdifferent from the extracted static objects exist at positionscorresponding to the position information of the static objectsconfirmed in the map data which is previously stored. In addition, as aresult of the examination, if the different objects exist, thecontrolling unit 305 reflects the extracted static objects to the mapdata which is previously stored corresponding to the positioninformation and update the map data to store it in the map data storingunit 320 a.

The images received by the image processing apparatus 300 from thevehicles positioned on the road according to an exemplary embodiment ofthe present invention include fixed geographic features, static objectssuch as lane information marked on the road such as left turn/rightturn, and dynamic objects such as other vehicles positioned on the road,pedestrians, and the like. Therefore, it is important to excludeunnecessary dynamic objects except for the static objects from theimages received when the image processing apparatus 300 generates orupdates the map data according to an exemplary embodiment of the presentinvention.

However, since the static objects in the received images are covered bythe dynamic objects, a case in which it is difficult for the imageprocessing apparatus 300 to identify the static objects may occur.Therefore, according to an exemplary embodiment of the presentinvention, in order to solve the above-mentioned problem, the imageprocessing apparatus 300 registers the reference image and the targetimage, performs the transparency process, and then extracts the staticobjects.

FIG. 12 is a diagram illustrating an operation of extracting staticobjects using the acquired images on an actual road according to anexemplary embodiment of the present invention.

In FIG. 12, a right turn lane marking 1201 exists on a road of referencenumeral 1205 but a vehicle exists on a road of reference numeral 1210 inwhich it is difficult to extract the right turn lane marking 1201. Inthis case, when the image processing is performed according to anexemplary embodiment of the present invention, the vehicle, which is thedynamic object, appears to be dim, but the extraction of the right turnlane marking 1201, which is the static object, may be easily identified,as in reference numeral 1215. Therefore, according to an exemplaryembodiment of the present invention, since the image processingapparatus 300 may confirm the right turn marking 1201 existing on theroad, it may update the map data so as to reflect the correspondingcontents when the right turn marking 1201 does not exist in the map datawhich is previously created.

The transmitting unit 315 transmits the map data stored in the storingunit 320 or the map data updated by the controlling unit 305 to theelectronic apparatus 200 of the vehicle or the smartphone of the user.Further, the transmitting unit 315 may also transmit a messagerequesting a transmission of images acquired at a current position tothe electronic apparatuses 200 of the vehicles.

Further, the exemplary embodiment of the present invention describesthat the transparency processing unit 320 e performs the transparencyprocess after the image registration is performed by the imageregistration unit 320 d, but is not limited thereto.

According to another exemplary embodiment of the present invention, thetransparency processing operation may also be performed afterdetermining the images to be registered by the controlling unit 305, mayalso be performed after the feature points are extracted, and may alsobe performed after the homography is calculated.

FIG. 13 is an operation flowchart of an image processing apparatusaccording to an exemplary embodiment of the present invention.

The image processing apparatus 300 receives images in an operation(S1305) and stores the received images in the storing unit in anoperation (S1310). In addition, the image processing apparatus 300determines the reference image and the target image in an operation(S1315) and performs an image pre-processing in an operation (S1320).The image pre-processing operation includes an image processing to unifythe color, brightness, and definition of the image so as not to beinfluenced by recognition of the image and a synthesizing process withother images, and mainly uses functions such as Curves, Levels,Brightness/Contrast, Color Balance, Shadows/Highlight, and the like.

If the image pre-processing operation is completed, the image processingapparatus 300 performs an image processing operation according to anexemplary embodiment of the present invention in an operation (S1325).The image processing operation performed in the operation (S1325) willbe descried with reference to FIG. 14.

If the image processing in the operation (S1325) is completed, the imageprocessing apparatus 300 extracts static objects from the registeredimage in an operation (S1330) and compares the extracted static objectswith the map data which is previously store in an operation (S1335).Specifically, the image processing apparatus 300 confirms whether or notobjects different from the extracted static objects exist at a positioncorresponding to position information of the static object confirmed inthe map data which is previously stored.

As a result of the confirmation of the operation (S1335), if the objectsdifferent from the static objects extracted from the map data which ispreviously stored exist in an operation (S1340), the image processingapparatus 300 update the map data in an operation (S1345) and transmitsthe updated map data to the electronic apparatus or the smartphone ofthe user in an operation (S1350).

FIG. 14 is a flowchart illustrating the operation (S1325) of FIG. 13 indetail.

The image processing apparatus 300 extracts first feature points fromthe reference image and extracts second feature points from the targetimage in an operation (S1405). In addition, the image processingapparatus 300 matches a first feature point group in which the firstextracted feature points are grouped and a second feature point group inwhich the second extracted feature points are grouped in an operation(S1410), and calculates a homography using information of matched pairsbetween the first feature point group and the second feature point groupin an operation (S1415).

The image processing apparatus 300 converts the target image using thehomography calculated in the operation (S1415) in an operation (1420),and registers the reference image and the converted target image in anoperation (S1425).

In addition, the image processing apparatus 300 performs thetransparency process for the registered images in an operation (S1430)and then synthesizes the transparency-processed images in an operation(S1435). The operation (S1435) is an optional operation and may not alsobe performed as needed. That is, when the image processing apparatus 300extracts the static objects from the registered images according to anexemplary embodiment of the present invention, the image processingapparatus 300 may also extract the static objects in a state in whichthe transparency process is completed and may also extract the staticobjects after the transparency process is performed and the imagesynthesis is also completed.

FIG. 15 is a block configuration diagram of an image processingapparatus for creating a map according to another exemplary embodimentof the present invention. An input unit 1550 may receive a command forperforming an operation of an image processing apparatus 1500 from theuser, and may include a keypad, a touch pad (resistive/capacitive), andthe like.

An image processing unit 1510 processes images received from thevehicles positioned on the road and extracts a variety of informationsuch as fixed geographic features, extending/closing of the road, orlane information such as a left turn/right turn from the receivedimages.

A communicating unit 1520 performs communication with electronicapparatuses or mobile terminals such as smartphones included in thevehicles to receive the photographed images or transmit created map datato the electronic apparatuses or the mobile terminals. The communicatingunit 1520 may perform communication in a wired communication scheme aswell as various wireless communication schemes such as Bluetooth, Wi-Fi,wireless broadband, 3rd generation (3G), WCDMA scheme, long termevolution (LTE), and a 4th generation (4G) communication schemes.

A storing unit 1530 stores the images received by the electronicapparatuses or the mobile terminals such as the smartphones included inthe vehicles, map data generated by a map creating server (not shown) orthe image processing apparatus 1500, and instructions which areexecutable by the controlling unit 340 of the image processing apparatus1500. As the storing unit 1530, various storing mediums such as a randomaccess memory (RAM), a static random access memory (SRAM), a read onlymemory (ROM), an electrically erasable programmable read-only memory(EEPROM), a programmable read-only memory (PROM), a magnetic memory, amagnetic disk, an optical disc, and the like may be used.

A controlling unit 1540 performs a control to process the received imageto generate the map data, or generate updated data for updating the mapdata, and transmit the generated map data to the electronic apparatusesor the mobile terminals such as the smartphones included in the vehiclesthrough the communicating unit 1520.

FIG. 16 is a method flowchart illustrating a method for creating a mapof the image processing apparatus of FIG. 15.

FIG. 16 relates to a case of updating map data which is previouslystored when driving paths of the vehicles driving on the road aredifferent from the map data which is previously stored. As an example, acase in which the road is a left turn no region on the map data which ispreviously stored, but the vehicle turns left, a case in which thevehicle is being driven even though there is no road in the map datawhich is previously stored, or the like may correspond to such asituation. Here, since the road or the lane information marked on theroad corresponds to the static object, the map which is previouslystored may be modified by the image processing method as describedabove.

Specifically, the image processing apparatus 1500 receives and stores avariety of data such as the images received from the electronicapparatuses of the vehicles driving on the road, user driving logs, andthe like in an operation (S1600). Next, in an operation (S1610), thecontrolling unit 1540 of the image processing apparatus 1500 confirmswhether or not there are different points between the map data such asthe road, the lane information, and the like stored in the map datawhich is previously stored and the user driving contents by analyzingthe user driving logs.

If there are the different points in an operation (S1620) (Yes inS1620), the controlling unit 1540 controls the image processingapparatus 1510 so as to perform the image processing for thecorresponding point and extracts static objects such as the road and thelane information for the corresponding point in an operation (S1630).Here, it is preferred that the image processing apparatus 1500 performsthe image processing operation when the images are acquired from theelectronic apparatuses of the plurality of vehicles which are driven atthe corresponding point.

Next, the controlling unit 1540 compares the extracted static objectswith the map data to confirm whether to necessary to modify data for thestatic objects included in the map data in an operation (S1640), andgenerates update information for modifying the map data when it isnecessary to modify the data for the static objects in an operation(S1650). The controlling unit 1540 modifies the map data using theupdate information generated in the operation (S1650) in an operation(S1660) and transmits the update information generated in the operation(S1660) to the electronic apparatuses of the vehicles which are drivenon the road. Here, the controlling unit 1540 may transmit the map datato the electronic apparatus capable of using the map data such as thesmartphone or the like through the communicating unit 1520 so that theuser may conveniently use the map data.

FIG. 17 is a block configuration diagram of an electronic apparatusaccording to still another exemplary embodiment of the presentinvention.

An input unit 1715 transmits a variety of control commands input fromthe user to a controlling unit 1705, and may be a touch screen panel, akeyboard, or a mouse. A communicating unit 1720 performs communicationwith the image processing apparatus according to an exemplary embodimentof the present invention or other electronic apparatuses. An output unit1725, which is a configuration for providing information to the user insound or visual way, may be a display or a speaker. A camera unit 1730photographs subjects by a control of the controlling unit 1705.

The image processing unit 1710 may perform image processing such asfeature point extraction, transparency process, or image registrationfor the images photographed by the camera unit 1730 as described in thepresent specification to allow the controlling unit 1705 to extract thestatic objects.

A storing unit 1735 stores instructions and map data which may beperformed by the controlling unit 1705 so that the electronic apparatus1700 may be operated.

In a case in which the vehicle in which the electronic apparatus 1700according to another exemplary embodiment of the present invention ismounted drives on the road, the controlling unit 1705 performs a controlso that the images are acquired through the camera unit 1730 and loadsthe map data stored in the storing unit 1735. In addition, thecontrolling unit 1705 performs a path guidance through the output unit1725 using the loaded map data and a position of the vehicle which iscurrently measured, and extracts the static objects by performing theimage processing for the images acquired by the camera unit 1730 by theimage processing unit 1710.

In addition, the controlling unit 1705 compares the extracted staticobjects with the map data, examines whether or not the extracted staticobjects exist in the map data used for the path guidance, and request anupdate of the map data stored in the storing unit 1735 to the imageprocessing apparatus through the communicating unit 1720 when theextracted static objects do not exist in the map data.

If the updated map data is received through the communicating unit 1720,the controlling unit 1735 updates the map data which is previouslystored in the storing unit 1735.

FIG. 18 is a flowchart of an operation of the electronic apparatus 1700of FIG. 17.

If the vehicle drives on the road (S1805), the electronic apparatus 1700installed in the vehicle acquires images in an operation (S1810) andloads map data in an operation (S1815). In addition, the electronicapparatus 1700 performs a path guidance using the loaded map data and aposition of the vehicle which is currently measured in an operation(S1820), and extracts static objects by performing an image processingfor the acquired images in an operation (S1825).

The electronic apparatus 1700 compares the extracted static objects withthe map data in an operation (S1830) and examines whether or not theextracted static objects exist in the map data used for the pathguidance in an operation (S1835). As a result of the examination of theoperation (S1835), if the static object different from the extractedstatic objects exist in the map data, the electronic apparatus 1700requests an update of the map data which is previously stored to theimage processing apparatus in an operation (S1840). If the updated mapdata is received in an operation (S1845), the electronic apparatus 1700updates the map data which is previously stored in an operation (S1850).

FIGS. 19 and 20 are diagrams illustrating a transparency process forfive images according to an exemplary embodiment of the presentinvention.

FIG. 19 illustrates a total of five images (reference numerals 1905,1910, 1915, 1920, and 1925) acquired at the same point according to anexemplary embodiment of the present invention and reference numerals2005, 2010, 2015, 2020, and 2025 of FIG. 20 illustrate results obtainedby performing a transparency process for each of the images of referencenumerals 1905, 1910, 1915, 1920, and 1925 of FIG. 19. Since the totalnumber of images to be targeted to the transparency process is 5 (N=5)in FIGS. 19 and 20, a constant multiplied with a pixel value of each ofthe images of reference numerals 1905, 1910, 1915, 1920, and 1925 ofFIG. 19 to perform the transparency process according to an exemplaryembodiment of the present invention is ⅕. That is, the respective imagesof FIG. 20 are the transparency-processed images obtained by multiplyingthe respective pixel values of the respective images of FIG. 19 by ⅕.

In addition, FIG. 21 is a diagram illustrating an image registration ofthe transparency-processed images of FIG. 20 and FIG. 22 is a diagramillustrating a result of the image registration of FIG. 21, where it maybe seen that the vehicles, which are the dynamic objects, disappear,while roads, lane marking lines, crosswalks, traffic lights, and thelike, which are static objects, exist as it is. According to the presentinvention, the static objects may be extracted from the images in thismethod and used to update or create the map data.

Meanwhile, the above-mentioned example illustrates that the transparencyprocessing unit performs the transparency process by multiplying therespective pixel values (0 to 255) of the transparency target images bya predetermined constant and performing the image processing so that therespective pixel values (0 to 255) of the transparency target imageshave a pixel value smaller than the original pixel values of the images,but is not limited thereto. According to another implementation of thepresent invention, the transparency processing unit may adjusttransparency of the corresponding image by adjusting an ALPHA (A) valuecorresponding to a transparency level in an RGBA value of thetransparency target image. Here, the Alpha (A) value may be defined inadvance and may also be updated periodically.

Further, the above-mentioned example illustrates that the static objectsand the dynamic objects are extracted from the registered image bycalculating the standard deviations of the pixel value of the registeredimage, the pixel value of the reference image, and the pixel value ofthe target image for each of the pixels, determining the pixels in whichthe calculated standard deviation is the predetermined value or less asthe pixels for the static objects, and determining the pixels in whichthe calculated standard deviation exceeds the predetermined value as thepixels for the dynamic objects, but is not limited thereto. According toanother implementation of the present invention, the static objects andthe dynamic objects may also be classified by comparing an ALPHA (A)value in an RGBA value of the registered image with a predeterminedtransparency value.

Meanwhile, the control method according to various exemplary embodimentsof the present invention described above may be implemented in a programso as to be provided to the server or devices. Accordingly, therespective apparatuses may be connected to the server or the device inwhich a program is stored to download the program.

Further, the control method according to various exemplary embodimentsof the present invention described above may be implemented in theprogram and be stored and provided in various non-transitorycomputer-readable mediums. The non-transitory readable medium is not amedium that stores data for a short period of time, such as a register,a cache, a memory, or the like, but means a medium that semi-permanentlystores data and is readable by a device. Specifically, the variousapplications or programs described above may be stored and provided inthe non-transitory computer readable medium such as a compact disk (CD),a digital versatile disk (DVD), a hard disk, a Blu-ray disk, a universalserial bus (USB), a memory card, a read only memory (ROM), or the like.

According to the various exemplary embodiments of the present inventiondescribed above, it is possible to extract static objects positioned onthe road through the images obtained by the cameras installed in thevehicles positioned on the road and to accurately and quickly create themap using the extracted static object.

Further, according to the various exemplary embodiments of the presentinvention described above, it is possible to remotely update the mapdata in real time by receiving the images obtained through the camerasof the vehicles positioned on the road in real time, unlike an existingmap creating system through a survey.

Further, according to the various exemplary embodiments of the presentinvention described above, it is possible to provide the map service towhich the newest road environment is applied to the users bytransmitting the map data which is updated in real time to the vehiclespositioned on the road.

Although exemplary embodiments of the present invention have beenillustrated and described hereinabove, the present invention is notlimited to the above-mentioned specific exemplary embodiments, but maybe variously modified by those skilled in the art to which the presentinvention pertains without departing from the scope and spirit of thepresent invention as disclosed in the accompanying claims. Thesemodifications should also be understood to fall within the scope of thepresent invention.

What is claimed is:
 1. An image processing method comprising: acquiringimages taken during driving of a moving object; performing first imageprocessing including image registration processing and transparencyprocessing of the acquired images; performing second image processing ofsynthesizing images on which the first image processing has beenperformed; and extracting a static object from an image generatedaccording to the second image processing.
 2. The image processing methodof claim 1, wherein the method further comprising: identifying a type ofthe extracted static object through deep learning or machine learning.3. The image processing method of claim 2, wherein the identifyingidentifies the type of the static object in order to select staticobject to be reflected in the map data among the extracted staticobject.
 4. The image processing method of claim 1, wherein the acquiredimages includes the static object and a dynamic object, wherein thestatic object comprises at least one of a bridge, a building, a road, asidewalk, a road construction mark, a speed bump, a crosswalk, aintersection, a traffic light, a median strip, a bus stop and adirectional sign, and wherein the dynamic object comprises at least oneof a vehicle and a pedestrian.
 5. The image processing method of claim1, wherein the image registration processing of the first imageprocessing comprising: determining a reference image and a target imageamong the acquired images; extracting a plurality of feature points fromeach of the determined reference image and target image; and matchingthe extracted plurality of feature points.
 6. The image processingmethod of claim 5, wherein the image registration processing of thefirst image processing further comprising: calculating a homography,which is a transformation matrix between the reference image and thetarget image, using information of matched pairs between first featurepoint group of the reference image and the second feature point group ofthe target image.
 7. The image processing method of claim 1, wherein thetransparency processing of the first image processing comprising:multiplying R, G, and B pixel values of respective pixels included inthe images for which the transparency processing is to be performed by apredetermined value smaller than 1, and wherein the predetermined valueis a reciprocal number of N, which is a total number of the images forwhich the transparency process is to be performed.
 8. The imageprocessing method of claim 7, wherein the extracting of the staticobject comprising: calculating standard deviations of a pixel value ofthe synthesized image, a pixel value of the reference image, and a pixelvalue of the target image for each of pixels; and determining pixels ofwhich the calculated standard deviation is a predetermined value or lessas pixels for the static object.
 9. The image processing method of claim1, wherein the transparency processing of the first image processingcomprising: performing the transparency processing by adjusting an ALPHA(A) value corresponding to a transparency level in an RGBA value of atransparency target image.
 10. The image processing method of claim 9,wherein the extracting of the static object comprising: extracting thestatic object by comparing an A(ALPHA) value in an RGBA value of thesynthesized image with a predetermined transparency value.
 11. An imageprocessing method comprising: an image acquiring unit acquiring imagestaken during driving of a moving object; an processor performing firstimage processing including image registration processing andtransparency processing of the acquired images, performing second imageprocessing of synthesizing images on which the first image processinghas been performed and extracting a static object from an imagegenerated according to the second image processing.
 12. The imageprocessing apparatus of claim 11, wherein the processor identifies atype of the extracted static object through deep learning or machinelearning.
 13. The image processing apparatus of claim 12, wherein theprocessor identifies the type of the static object in order to selectstatic object to be reflected in the map data among the extracted staticobject.
 14. The image processing apparatus of claim 11, wherein theacquired images includes the static object and a dynamic object, whereinthe static object comprises at least one of a bridge, a building, aroad, a sidewalk, a road construction mark, a speed bump, a crosswalk, aintersection, a traffic light, a median strip, a bus stop and adirectional sign, and wherein the dynamic object comprises at least oneof a vehicle and a pedestrian.
 15. The image processing apparatus ofclaim 11, wherein in the image registration processing of the firstimage processing, the processor determines a reference image and atarget image among the acquired images, extracts a plurality of featurepoints from each of the determined reference image and target image andmatches the extracted plurality of feature points.
 16. The imageprocessing apparatus of claim 15, wherein in the image registrationprocessing of the first image processing, the processor calculates ahomography, which is a transformation matrix between the reference imageand the target image, using information of matched pairs between firstfeature point group of the reference image and the second feature pointgroup of the target image.
 17. The image processing apparatus of claim11, wherein in the transparency processing of the first imageprocessing, the processor multiplies R, G, and B pixel values ofrespective pixels included in the images for which the transparencyprocessing is to be performed by a predetermined value smaller than 1,and wherein the predetermined value is a reciprocal number of N, whichis a total number of the images for which the transparency process is tobe performed.
 18. The image processing apparatus of claim 17, wherein inthe extracting of the static object, the processor calculates standarddeviations of a pixel value of the synthesized image, a pixel value ofthe reference image, and a pixel value of the target image for each ofpixels, and determines pixels of which the calculated standard deviationis a predetermined value or less as pixels for the static object. 19.The image processing apparatus of claim 11, wherein in the transparencyprocessing of the first image processing, the processor performs thetransparency processing by adjusting an ALPHA (A) value corresponding toa transparency level in an RGBA value of a transparency target image.20. A non-transitory computer readable recording medium in which aprogram for executing an image processing method is recorded, the imageprocessing method comprising: acquiring images taken during driving of amoving object; performing first image processing including imageregistration processing and transparency processing of the acquiredimages; performing second image processing of synthesizing images onwhich the first image processing has been performed; and extracting astatic object from an image generated according to the second imageprocessing.